Applied AI and Business Enablement Director (E6116)

Job Summary 
The Director, Applied AI & Business Enablement is a newly created, high-visibility leadership role within the Data & Analytics organization. Reporting to the Chief Data Officer, this leader will serve as the primary bridge between the enterprise's data and AI capabilities and its business partners, driving AI adoption, literacy, and strategic value realization across the organization.

This is not a model-building or tool-development role. The ideal candidate is a practitioner and evangelist—someone with deep, hands-on fluency in modern AI tools (large language models, copilots, agentic frameworks, and no-code/low-code AI platforms) who can translate that expertise into business impact. They will partner directly with senior business leaders to identify high-value AI opportunities, upskill teams, and shape the organization's applied AI roadmap.

This role sits as a peer to the Directors of Enterprise Data Science, Commercial Data Science, Data Governance, and Data Engineering, serving as the connective tissue between what those teams build and what the business needs.


Key Responsibilities

• How You Will Make An Impact
• AI Literacy & Business Upskilling
• Design and deliver enterprise-wide AI education programs tailored to business audiences—executives, functional leaders, and individual contributors
• Teach business partners how to effectively interact with data and AI tools, including prompt engineering, evaluating AI outputs, and understanding tool capabilities and limitations.
• Develop reusable enablement assets: playbooks, quick-reference guides, training curricula, and use-case libraries.
• Run workshops, office hours, and hands-on demonstrations that build confidence and competence across the organization.
• Build and manage an AI Champion Network—a distributed group of power users embedded in business units who accelerate peer-to-peer adoption.
• Use Case Discovery & POC Prioritization
• Work with business units to deeply understand workflows, pain points, and strategic objectives.
• Surface high-value AI use cases that may not be immediately obvious to business partners, contributing an applied AI lens to the broader discovery process
• Contribute to AI opportunity evaluation within the prioritization frameworks being developed within IEEE to ensure AI POCs are assessed using consistent criteria
• Agentic AI Roadmapping
• Continuously evaluate the evolving landscape of agentic AI—autonomous workflows, multi-step AI agents, and intelligent automation—and translate trends into enterprise-relevant opportunities.
• Identify processes and workflows across the organization that would benefit from agentic AI, distinguishing between where human-in-the-loop augmentation vs. autonomous execution is appropriate.
• Develop the organization’s applied agentic AI roadmap in partnership with the CDO and peer Directors, including recommended pilots and phased deployment strategies.
• Serve as the organization’s subject matter expert on agentic tools and frameworks, advising on vendor capabilities, integration patterns, and readiness requirements.
• AI Governance Liaison
• Partner closely with the Director of Data Governance to ensure all enablement activities, POCs, and deployed use cases operate within established data governance and responsible AI guardrails.
• Advocate for governance as an enabler (not a blocker) of AI adoption, helping business partners understand policies around data privacy, bias mitigation, model transparency, and acceptable use.
• Contribute to the development and evolution of AI governance policies by bringing front-line feedback from business adoption efforts.
• Ensure that all AI enablement programs incorporate responsible AI principles, including fairness, explainability, and human oversight.

Travel Information

• 15% Domestic and International